Seismic data is collected and processed in the oil industry as a means of imaging a potential geological target for subsequent drilling. Sophisticated computers and modeling software now allow for the careful pre-survey testing of actual field acquisitions scenarios prior to actually sending a crew out to collect a new dataset. Careful testing and computer modeling of the survey offer the potential of saving large sums of money by collecting only the data needed and nothing else, or by avoiding methodologies that can't image the geologic target desired.
One of the problems with computer modeling is that in general the models are not perfectly accurate and precise and do not adequately represent the geology that is being imaged. Because the models are not accurate enough they give misleading results. At the same time, processing of actual field data from a survey tends to lead to very complex images that are contaminated with noise and artifacts that also cause misleading interpretations and results. The problem is how one determines what information is critical and what portion of the model is not accurately represented and causing misleading results.
For the construction of the model, a source signal is propagated through the earth model into the various subsurface layers. Here elastic waves are formed through interaction with the modeled geologic structures in the subsurface layers. Elastic waves are characterized by a change in local stress in the subsurface layers and a particle displacement, which is essentially in the same plane as the wavefront. Acoustic and elastic waves are also known as pressure and shear waves. Acoustic and elastic waves are collectively referred to as the seismic wavefield.
A reflected wavefield may consist of both primary reflections and multiple reflections. Primary reflections may be defined as seismic waves that have reflected only once, from an interface between subterranean formations, before being detected by a seismic receiver. Primary reflections contain the desired information about the subterranean formations that are the goal of seismic surveying. Multiple reflections, or multiples, may be defined as seismic waves that have reflected more than once before being detected by a seismic receiver and depending on the processing algorithms maybe considered additional signal or noise in the dataset.
The measurements acquired in the seismic acquisition are then used to model wave propagation. When an acoustic wave impinges a boundary between two different subsurface materials that have different acoustic transparencies and acoustic impedances, some of the energy of the acoustic wave is transmitted or refracted through the boundary, while some of the energy is reflected off the boundary. This energy that is transmitted and reflected or refracted can either contribute to the image or degrade it, depending on how it is processed.
Often, the cause of inadequate imaging of deep structures lies in the presence of geologic complexity above the target objective. Variations in topography and in the velocity of these shallower layers create distortions in the seismic signal. Strongly refractive layers near the surface can prevent deep penetration of seismic energy, as can intervals of anomalously low velocity. Abrupt lateral changes in near-surface properties can warp raypaths and weaken the effectiveness of traditional processing methods. Locations with rough topography, shallow gas pockets, surface dunes, permafrost and buried soft layers are notorious for the obstacles they present to exploration. Additionally, velocity anomalies within the earth at depth can warp raypaths and create distortions in the seismic signal that are hard to identify with current processing methods.
Thus, in the modeling and processing of seismic data, there exists a flaw in boundary conditions of the various geologic horizons that are typically applied to such data. To keep the size of the computer model within practicable bounds, only a small portion of the ground influenced by the source can be mapped onto a computational domain, while the rest has to be captured by an artificial boundary condition. The flaw in the current modeling method is that unless the earth model is perfect, or in places where there exist errors, the energy propagates through those errors and corrupts the remaining image outside the zone of error leading the interpreter to incorrectly assume that the model is much more accurate than it really is.
Therefore, there is the need for an earth modeling method that avoids any distortions caused by areas where the earth model cannot be accurately determined by altering the typical boundary condition associated with such areas.